Recent advances in human molecular genetics and genetic epidemiology can allow the successful genetic dissection of complex diseases. For disorders with an unknown biochemical basis, identification of the genes is a prerequisite to their understanding of its biological basis. Nowhere can this success be more helpful than in psychiatric diseases. This application for a Multi-Institutional Collaborative Research Project (MICRP) is designed to identify regions of the human genome involved in susceptibility to schizophrenia. It involves a collaborative effort between groups at the University of Pittsburgh and Case Western Reserve University. This research is proposed as a research paradigm for the genetic dissection of multigenic disorders. Schizophrenia is a severe psychiatric illness with a lifetime morbid risk of approximately 1 percent. Its precise etiology is unknown and treatment remains palliative. A significant inherited predisposition has been established, but the mode of inheritance is uncertain. In this application the investigators propose contemporary methods in research design, family ascertainment, genotyping and linkage/association analyses to dissect the genetic factors in schizophrenia. The investigators propose to ascertain a large sample of nuclear families with affected individuals. The families will include those with one ill individual, as well as those with two or more affected. Linkage analysis will be conducted initially using the affected sib-pairs. State-of-the-art genotyping of highly polymorphic anonymous markers spaced at 10 cM intervals throughout the genome and novel statistical genetic analysis will be used to identify regions spanning susceptibility loci. Such regions will be further investigated using more densely spaced markers and parents of probands. Subsequently, anonymous markers and those of candidate genes thought to be linked to the disease genes will be further evaluated using the haplotype relative risk (HRR) and transmission disequilibrium test (TDT) methods. The combined linkage and association approach are a powerful combination for investigating the genetic basis of disease.